3 papers
quant-ph2026
On linearity or non-linearity in machine learning for quantum chaotic dynamics
Francesco Perciavalle, Agostino Gallo, Francesco Plastina +3
Accurately simulating chaotic quantum many-body dynamics remains a major computational challenge for classical methods, due to the rapid buildup and spatial spreading of entangleme…
cs.LG2025
Advancing Wildfire Risk Prediction via Morphology-Aware Curriculum Contrastive Learning
Fabrizio Lo Scudo, Alessio De Rango, Luca Furnari +4
Wildfires significantly impact natural ecosystems and human health, leading to biodiversity loss, increased hydrogeological risks, and elevated emissions of toxic substances. Clima…
eess.IV2024
μ-Net: A Deep Learning-Based Architecture for μ-CT Segmentation
Pierangela Bruno, Edoardo De Rose, Carlo Adornetto +12
X-ray computed microtomography (μ-CT) is a non-destructive technique that can generate high-resolution 3D images of the internal anatomy of medical and biological samples. These im…